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Prompts

A prompt is a message template the user picks.

Tools are for the model. A prompt is the opposite: the user chooses one from a menu in their client (a slash command, a button), fills in its arguments, and the rendered messages go into the conversation as if they had typed them.

You declare one by putting @mcp.prompt() on a function that returns the text.

Your first prompt

server.py
from mcp.server import MCPServer

mcp = MCPServer("Code Helper")


@mcp.prompt()
def review_code(code: str) -> str:
    """Review a piece of code."""
    return f"Please review this code:\n\n{code}"

The SDK reads the same three things it read from your tools:

  • The name is the function name: review_code.
  • The description the client shows is the docstring: Review a piece of code.
  • The arguments come from the parameters. code has no default, so it's required.

That is what a client gets back from prompts/list:

{
  "name": "review_code",
  "description": "Review a piece of code.",
  "arguments": [
    {"name": "code", "required": true}
  ]
}

There is no JSON Schema here. Prompt arguments are a flat list of named string values: a form a person fills in, not a payload a model constructs.

Rendering it

The client renders the template with prompts/get, passing the arguments. Your function runs and the str you return becomes one user message:

{
  "description": "Review a piece of code.",
  "messages": [
    {
      "role": "user",
      "content": {
        "type": "text",
        "text": "Please review this code:\n\ndef add(a, b): return a + b"
      }
    }
  ],
  "resultType": "complete"
}

That is the entire life of a prompt: listed by name, rendered on demand, dropped into the chat.

Check

required is enforced before your function runs. Render review_code without code and the request itself fails with a JSON-RPC error (code -32603):

mcp.shared.exceptions.MCPError: Internal server error

There is no tool-style error result to hand back to a model, because no model is in the loop: the call raises. The reason (Missing required arguments: {'code'}) lands in your server's log.

Try it

Run the server with the MCP Inspector:

uv run mcp dev server.py

Open the Prompts tab and select review_code. The Inspector draws a form with one required code field. Fill it in, render it, and you get back exactly the user message above.

More than one message

A code review is one message. A debugging session is a conversation, and a prompt can seed the whole thing.

Return a list of messages instead of a str:

server.py
from mcp.server import MCPServer
from mcp.server.mcpserver.prompts.base import AssistantMessage, Message, UserMessage

mcp = MCPServer("Code Helper")


@mcp.prompt()
def review_code(code: str) -> str:
    """Review a piece of code."""
    return f"Please review this code:\n\n{code}"


@mcp.prompt()
def debug_error(error: str) -> list[Message]:
    """Start a debugging conversation."""
    return [
        UserMessage("I'm seeing this error:"),
        UserMessage(error),
        AssistantMessage("I'll help debug that. What have you tried so far?"),
    ]
  • UserMessage and AssistantMessage come from mcp.server.mcpserver.prompts.base. Hand them a str and they wrap it in TextContent for you. The role is the class name.
  • Message is their common base. Use it as the return annotation.

Rendering debug_error now produces three messages, in order:

{
  "description": "Start a debugging conversation.",
  "messages": [
    {"role": "user", "content": {"type": "text", "text": "I'm seeing this error:"}},
    {"role": "user", "content": {"type": "text", "text": "TypeError: 'int' object is not iterable"}},
    {
      "role": "assistant",
      "content": {"type": "text", "text": "I'll help debug that. What have you tried so far?"}
    }
  ],
  "resultType": "complete"
}

Notice the last one. Pre-filling an assistant turn is how you steer the model's next reply without making the user type the steering themselves.

Titles and argument descriptions

review_code is a function name, not a label. Give the client something better to put on the button, and describe each argument so the form explains itself:

server.py
from typing import Annotated

from pydantic import Field

from mcp.server import MCPServer

mcp = MCPServer("Code Helper")


@mcp.prompt(title="Code review")
def review_code(
    code: Annotated[str, Field(description="The code to review.")],
    language: Annotated[str, Field(description="The language the code is written in.")] = "python",
) -> str:
    """Review a piece of code."""
    return f"Please review this {language} code:\n\n{code}"
  • title="Code review" is the human-readable name, exactly like a tool's title.
  • Annotated[str, Field(description=...)] is the same pattern you used in Tools. Here the description lands on the argument instead of in a schema.
  • language has a default, so it stops being required.

The prompts/list entry now carries everything a client needs to draw a good form:

{
  "name": "review_code",
  "title": "Code review",
  "description": "Review a piece of code.",
  "arguments": [
    {"name": "code", "description": "The code to review.", "required": true},
    {"name": "language", "description": "The language the code is written in.", "required": false}
  ]
}

Info

If you have read Tools, you already know everything on this page. Same decorator, same docstring-as-description, same Annotated/Field. The only things that change are who triggers it (the user) and where the result goes (into the conversation).

Recap

  • @mcp.prompt() on a function makes it a prompt. Name from the function, description from the docstring.
  • Prompts are user-controlled: the client lists them, the user picks one and fills in the arguments.
  • Arguments are a flat list of named strings (no schema). A parameter with a default is optional.
  • Return a str and it becomes one user message. Return a list of UserMessage / AssistantMessage to seed a multi-turn conversation.
  • title= and Field(description=...) are what a client puts in its UI.
  • A missing required argument fails the whole request. There is no per-prompt error result.

Next up: the one extra parameter a tool, resource or prompt can ask the SDK for, The Context.